class_docstr: Standalone Multiply-and-accumulate metric. Provides a lower bound of the
  computational cost of a model in a hardware-independent way by
  computing the number of multiplications. Currently supports only
  Linear or Conv2d modules. Other operations are ignored.
docstr: Return the number of MAC operations as computed in the previous call
  to the `update` method.
  
  :return: The number of MAC operations or None if `update` has not been
      called yet.
docstr_tok: ["Return","the","number","of","MAC","operations","as","computed","in","the","previous","call","to","the","`","update","`","method",".",":","return",":","The","number","of","MAC","operations","or","None","if","`","update","`","has","not","been","called","yet","."]
code: def result(self) -> Optional[int]:
      """
      Return the number of MAC operations as computed in the previous call
      to the `update` method.
  
      :return: The number of MAC operations or None if `update` has not been
          called yet.
      """
      return self._compute_cost
  
imports: from torch.nn import Module
  from typing import List, Optional
  from torch import Tensor
  from avalanche.evaluation import Metric, PluginMetric, GenericPluginMetric
label_desc: Use image node_id 3 for calling the MAC obj's underlying member method code with example usage: obj.result() and returns: self